Business Software for Cursor

Modern engineering teams have a math problem: AI coding assistants now produce the majority of new code, but the security stack underneath was built for an era when humans typed every line. Plexicus rewires that equation. We're an AI-native ASPM platform with Vibe Coding Security at its core — the first end-to-end solution that meets developers where they actually work, whether they're writing code by hand or pair-programming with Cursor, Claude Code, Copilot, Windsurf, Devin, Replit, Zed, or VS Code (JetBrains coming). What sets Plexicus apart isn't another dashboard of findings. It's the autonomous remediation loop: every detected risk arrives with a GenAI-generated pull request that fixes the root cause, lands in the developer's normal Git workflow, and clears triage queues before they form.

Palmier Pro is an AI-first video editor designed for creators and teams that want to generate media and edit finished videos in one timeline. Instead of creating clips on separate AI websites, downloading files, and importing them into another editor, users can generate AI images, video, and audio directly inside Palmier Pro. The platform includes professional editing tools for multi-track video, audio, image, and text projects. Users can trim clips, split footage, change speed, adjust opacity, transform assets, and combine traditional footage with AI-generated media. Palmier Pro integrates with leading AI models, including Kling, Seedance, Veo, Grok Imagine, and other supported generation tools. It also supports export workflows for Premiere Pro and DaVinci Resolve when users need to continue editing in established production environments. Through MCP, users can connect existing agents so they can generate media and work directly in a project’s timeline. The software is available for macOS and is positioned for production-ready AI video creation rather than simple clip generation alone. Palmier Pro gives video creators a faster way to move from AI generation to polished edits without breaking the creative workflow.

ToolSDK.ai is a complimentary TypeScript SDK and marketplace designed to expedite the development of agentic AI applications by offering immediate access to more than 5,300 MCP (Model Context Protocol) servers and modular tools with just a single line of code. This capability allows developers to seamlessly integrate real-world workflows that merge language models with various external systems. The platform provides a cohesive client for loading structured MCP servers, which include functionalities like search, email, CRM, task management, storage, and analytics, transforming them into tools compatible with OpenAI. It efficiently manages authentication, invocation, and the orchestration of results, enabling virtual assistants to interact with, compare, and utilize live data from a range of services such as Gmail, Salesforce, Google Drive, ClickUp, Notion, Slack, GitHub, and various analytics platforms, as well as custom web search or automation endpoints. Additionally, the SDK comes with example quick-start integrations, supports metadata and conditional logic for multi-step orchestrations, and facilitates smooth scaling to accommodate parallel agents and intricate pipelines, making it an invaluable resource for developers aiming to innovate in the AI landscape. With these features, ToolSDK.ai significantly lowers the barriers for developers to create sophisticated AI-driven solutions.

Gram is a versatile open-source platform designed to empower developers in the seamless creation, curation, and hosting of Model Context Protocol (MCP) servers, effectively converting REST APIs through OpenAPI specifications into tools ready for AI agents without necessitating any code modifications. The platform takes users through a structured workflow that includes generating default tools from API endpoints, narrowing down to relevant functionalities, crafting advanced custom tools by linking multiple API calls, and enriching these tools with contextual prompts and metadata, all of which can be tested instantly in an interactive environment. Additionally, Gram features built-in support for OAuth 2.1, which encompasses both Dynamic Client Registration and user-defined authentication flows, ensuring that agent access remains secure and reliable. Once these tools are fully developed, they can be deployed as robust MCP servers suitable for production, complete with centralized management functionalities, role-based access controls, detailed audit logs, and an infrastructure designed for compliance, which includes deployment at Cloudflare's edge and DXT-packaged installers that facilitate straightforward distribution. This comprehensive approach not only simplifies the development process but also enhances the overall functionality and security of the deployed tools, making it an invaluable resource for developers aiming to leverage AI technology effectively.

Simpliflow AI focuses on Loop, a centralized Model Context Protocol (MCP) gateway that streamlines the integration of various AI agents and tools into a single, orchestrated framework. Loop allows users to connect external MCP servers and integrate multiple applications in a one-time setup; subsequently, instead of incorporating every tool schema into the language model context—which can lead to cumbersome prompts—Simpliflow intelligently fetches and executes the required tool only in response to specific queries. This strategy maintains compact LLM contexts and prevents the risk of exceeding tool limits. Furthermore, Loop provides a comprehensive dashboard for managing all integrations and MCP connections, boasts over 1,500 pre-built integrations through managed OAuth, and ensures compatibility with any AI application that supports MCP. It also implements schema validation and integrity checks for enhanced security and reliability, granting advanced users detailed control while fostering a safer, cohesive environment for AI-driven workflows. In this way, Simpliflow AI not only optimizes performance but also enhances user experience through efficient management of AI resources.

Vivgrid serves as a comprehensive development platform tailored for AI agents, focusing on critical aspects such as observability, debugging, safety, and a robust global deployment framework. It provides complete transparency into agent activities by logging prompts, memory retrievals, tool interactions, and reasoning processes, allowing developers to identify and address any points of failure or unexpected behavior. Furthermore, it enables the testing and enforcement of safety protocols, including refusal rules and filters, while facilitating human-in-the-loop oversight prior to deployment. Vivgrid also manages the orchestration of multi-agent systems equipped with stateful memory, dynamically assigning tasks across various agent workflows. On the deployment front, it utilizes a globally distributed inference network to guarantee low-latency execution, achieving response times under 50 milliseconds, and offers real-time metrics on latency, costs, and usage. By integrating debugging, evaluation, safety, and deployment into a single coherent framework, Vivgrid aims to streamline the process of delivering resilient AI systems without the need for disparate components in observability, infrastructure, and orchestration, ultimately enhancing efficiency for developers. This holistic approach empowers teams to focus on innovation rather than the complexities of system integration.

Storm MCP serves as an advanced gateway centered on the Model Context Protocol (MCP), facilitating seamless connections between AI applications and multiple verified MCP servers through a straightforward one-click deployment process. It ensures robust enterprise-level security, enhanced observability, and easy integration of tools without the need for extensive custom development. By standardizing AI connections and only exposing specific tools from each MCP server, it helps minimize token consumption and optimizes the selection of model tools. With its Lightning deployment feature, users can access over 30 secure MCP servers, while Storm efficiently manages OAuth-based access, comprehensive usage logs, rate limitations, and monitoring. This innovative solution is crafted to connect AI agents to external context sources securely, allowing developers to sidestep the complexities of building and maintaining their own MCP servers. Tailored for AI agent developers, workflow creators, and independent innovators, Storm MCP stands out as a flexible and configurable API gateway, simplifying infrastructure challenges while delivering dependable context for diverse applications. Its unique capabilities make it an essential tool for those looking to enhance their AI integration experience.

Glazed Analytics is an innovative product analytics solution that leverages artificial intelligence to convert Figma design interfaces into actionable tracking plans. By analyzing design screens and integrating your existing event taxonomy, it offers suggestions for pertinent tracking events that users can choose to approve, modify, or decline. This tool generates prompts that are compatible with AI coding assistants, facilitating the deployment of feature tracking without needing extensive developer involvement. Additionally, the platform seamlessly incorporates visual documentation within Figma, embedding tracking specifications into design elements to serve as a centralized source of truth, effectively replacing scattered spreadsheets or Confluence documents. When connected to data warehouses like BigQuery, Redshift, and Snowflake, as well as analytics tools such as Amplitude, Mixpanel, and PostHog, Glazed delivers quality assurance views that highlight any missing or faulty event properties while providing first-seen and volume metrics. It also includes features that automatically check for duplicate naming and allows users to sync the history of design versions, ensuring a streamlined and efficient workflow throughout the product development process. This comprehensive approach not only enhances team collaboration but also optimizes the overall analytics pipeline.

TimeFly is a background coding activity tracker designed to unobtrusively gather detailed metrics on developers' usage of their integrated development environments (IDEs), without the need for buttons or timers. It effectively identifies top projects, programming languages, devices, and editors while also producing an activity heatmap along with statistics for coding sessions, such as average focus, peak activity times, and interruptions, all tailored for specific timeframes. By consolidating event streams from various IDEs and devices, TimeFly prevents duplication and fragmentation of data, seamlessly integrating it into a cohesive timeline. Users can access their information through import/export options or an API, and they also receive notifications, email reports, or security alerts to stay informed. The platform prioritizes transparency and security throughout its operations, ensuring users are aware of how their data is handled. Currently in its beta phase, TimeFly grants users access to a year’s worth of free historical data, and future updates are expected to introduce features such as goal-setting, enhanced project insights, team dashboards, and more comprehensive reporting tools. Additionally, the continuous development of the platform signifies a commitment to adapting to user needs and improving their coding experience.

SVGMaker is an innovative platform that leverages artificial intelligence to assist users in creating, transforming, and manipulating SVG files using natural language commands along with user-friendly editing tools. It offers export options in various vector formats, including SVG, PDF, EPS, AI, and DXF, as well as popular raster formats like PNG, JPG, and WebP. Users can design unique logos, adaptable web graphics, user interface components, print-ready designs, files for vinyl and laser cutting, as well as items for paper crafts. The platform features capabilities for converting images to SVG, editing SVG files, and optimizing vector graphics to enhance performance. One standout aspect of SVGMaker is its "MCP server" functionality, which seamlessly integrates into developer environments such as VS Code or Cursor, automatically identifying the need for graphic assets while you code and generating relevant SVGs that are tailored to your specific design requirements. Additionally, all files are stored in the cloud, with editing and conversion actions being managed through a credit-based system. The platform also equips users with advanced tools for controlling style and detail, interpreting prompts effectively, and ensuring outputs are compatible with clean coding practices, enhancing the overall design workflow. This makes SVGMaker an essential tool for both designers and developers looking to streamline their graphic asset creation process.

GolfMCP serves as an open-source framework aimed at simplifying the development and deployment of production-ready Model Context Protocol (MCP) servers, which empowers organizations to construct a secure and scalable infrastructure for AI agents without the hassle of boilerplate code. Developers can effortlessly define tools, prompts, and resources using straightforward Python files, while Golf takes care of essential tasks like routing, authentication, telemetry, and observability, allowing you to concentrate on the core logic rather than underlying plumbing. The platform incorporates enterprise-level authentication methods such as JWT, OAuth Server, and API keys, along with automatic telemetry and a file-based organization that removes the need for decorators or manual schema configurations. It also features built-in utilities that facilitate interactions with large language models (LLMs), comprehensive error logging, OpenTelemetry integration, and deployment tools like a command-line interface with commands for initializing, building, and running projects. Furthermore, Golf includes the Golf Firewall, a robust security layer tailored for MCP servers that enforces strict token validation to enhance the overall security framework. This extensive functionality ensures that developers are equipped with everything they need to create efficient AI-driven applications.

Fusion serves as an AI-driven development platform that seamlessly merges design, product management, and engineering processes by linking directly to your codebase, design system, and tools. This innovative platform empowers teams to visually create and modify responsive, production-ready user interfaces by utilizing existing repositories, design tokens, and APIs; users can easily import Figma designs, connect their GitHub or other Git providers, and issue changes using natural language, which the system converts into pull requests or live previews. It features real-time canvas editing with exceptional pixel precision, comprehends your components, styles, and backend architecture, and allows any team member—including designers, project managers, and developers—to construct features, prototypes, and fully interactive experiences without the need to manually code each element. With built-in workflow integration, users can trigger builds through Slack mentions, Jira tickets, or discussions around design, while also tracking progress, reviewing generated branches, and merging into standard CI/CD pipelines. This streamlined approach not only enhances collaboration but also increases efficiency across teams, making the development process more intuitive and accessible for everyone involved.

GPT-5.1-Codex is an advanced iteration of the GPT-5.1 model specifically designed for software development and coding tasks that require autonomy. The model excels in both interactive coding sessions and sustained, independent execution of intricate engineering projects, which include tasks like constructing applications from the ground up, enhancing features, troubleshooting, conducting extensive code refactoring, and reviewing code. It effectively utilizes various tools, seamlessly integrates into developer environments, and adjusts its reasoning capacity based on task complexity, quickly addressing simpler challenges while dedicating more resources to intricate ones. Users report that GPT-5.1-Codex generates cleaner, higher-quality code than its general counterparts, showcasing a closer alignment with developer requirements and a reduction in inaccuracies. Additionally, the model is accessible through the Responses API route instead of the conventional chat API, offering different configurations such as a “mini” version for budget-conscious users and a “max” variant that provides the most robust capabilities. Overall, this specialized version aims to enhance productivity and efficiency in software engineering practices.

Snippets AI serves as an innovative platform for managing AI prompts and code snippets, allowing users to easily store, modify, and utilize their prompts across various large language models from a single, cohesive workspace. It enhances efficiency by providing keyboard shortcuts that enable prompt insertion into any application without the need for copy and paste, promoting both speed and uniformity. Collaborative features are built-in, allowing teams to work together in shared environments with tools such as version control, syntax highlighting, voice input, and the option to share libraries either publicly or privately, which keeps everyone aligned on various content, templates, or coding structures. Additionally, Snippets AI includes developer-friendly REST APIs for the programmatic management of prompts, code, workspaces, and integrations, making it a versatile tool for developers. The platform also fosters a community-oriented approach with public libraries of handpicked prompts and a “Share & Earn” system that compensates creators based on the views their prompts receive. Moreover, it prioritizes enterprise-grade security through features like detailed permissions, audit logs, and tailored policies to safeguard data, ensuring that user information remains protected at all times. With these robust capabilities, Snippets AI stands out as a comprehensive solution for prompt and snippet management in the evolving landscape of AI technology.

Emdash serves as an orchestration layer that allows you to execute numerous coding agents simultaneously, each within its own distinct Git worktree, enabling you to address various subtasks or experiments concurrently without any interference. It is designed to be provider-agnostic, allowing you to select from a range of AI models and command-line interfaces, such as Claude Code and Codex, tailored to your specific workflow requirements. With Emdash, you can directly assign issues or tickets from platforms like Linear, GitHub, or Jira to a selected agent, enabling you to observe multiple agents working in parallel in real time. The user interface provides live updates on agent status and activities, and as soon as agents produce code, you can easily review differences, add comments, and initiate pull requests, all within the Emdash environment. Each agent operates within its own worktree, ensuring changes remain isolated and comparable, which facilitates safe testing of various implementations or strategies side by side. This unique setup not only enhances productivity but also encourages experimentation without the risk of code conflicts.

Atono is a product knowledge and workflow platform designed to help AI tools, product teams, and engineering teams work from the same product context. The platform addresses the problem of AI-generated specs, stories, and code being close but inaccurate because the AI lacks product-specific terminology, decisions, and implementation history. Atono builds product knowledge through three layers: a Glossary, Living Stories, and AI Context. The Glossary captures the product’s vocabulary, concepts, personas, and relationships from existing documentation so AI tools use the right terminology. Living Stories keep decisions, feedback, implementation notes, usage analytics, and feature flags attached to each story as the product evolves. AI Context captures design decisions, technical investigations, and implementation changes through Atono’s MCP server so tools like Cursor, Claude, and Copilot can continue from prior sessions. Teams can use Atono to plan, build, deploy, and measure work from the same story while keeping requirements, code context, release controls, and engagement data connected. The platform can operate as an intelligence layer alongside Jira, Linear, or an existing stack, or as a full platform that replaces project management, feature flag, and analytics tools. By combining product knowledge, AI context, stories, feature flags, analytics, MCP integrations, and cross-functional workflows, Atono helps teams make AI output more accurate and product work more connected.

FlowLens is an innovative debugging and session-recording tool driven by AI, designed to capture all essential elements required for accurate and context-sensitive bug diagnosis, while enabling AI coding agents to autonomously resolve issues. Through an easy-to-use browser extension and an optional MCP server, FlowLens documents comprehensive user sessions, recording video of the user interface, network requests, console logs, user actions (such as clicks and inputs), storage states (including cookies and local/session storage), and system information, all meticulously aligned on a cohesive timeline. After a bug is replicated, FlowLens compiles this complete context into a single "flow" that can be easily shared through a link. Compatible AI coding agents that work with MCP, including those from leading providers, can then access the flow to review network activities, error logs, UI states, and user inputs, facilitating automatic root cause analysis and code fix suggestions or generation. This streamlined process eliminates the tedious tasks of manual replays, the hassle of copying and pasting logs, and the need for lengthy bug descriptions, ultimately enhancing productivity and efficiency. Additionally, FlowLens empowers teams to focus on more complex problems, as the platform simplifies the debugging workflow, allowing developers to leverage AI effectively.

BrainGrid is an innovative software planning and requirements platform powered by artificial intelligence that assists developers in transforming initial concepts and abstract ideas into detailed specifications, organized tasks, and specific prompts tailored for AI coding agents like Cursor, Claude Code, and Replit, enabling the creation of dependable software rather than unstable prototypes. The process begins with an in-depth examination of your current codebase, encompassing its architecture, data structures, and interdependencies, followed by a collaborative effort to define the project scope, pose pertinent questions, and enhance conceptual descriptions into comprehensive, code-aware requirements. Subsequently, BrainGrid dissects these requirements into manageable, verifiable tasks that include context, objectives, dependencies, and acceptance criteria, producing prompts aimed at guiding AI coding tools effectively and significantly boosting the chances of achieving accurate execution on the first attempt. Furthermore, it facilitates automatic task generation, ongoing refinement of specifications, and seamless integration with various AI coding workflows, ensuring a more streamlined development process and improved software quality overall. This comprehensive approach not only enhances efficiency but also empowers teams to innovate and deliver high-quality products faster.

Repo Prompt is an AI coding assistant designed specifically for macOS, which serves as a context engineering tool that empowers developers to interact with and refine codebases through the use of large language models. By enabling users to select particular files or directories, it allows for the creation of structured prompts that contain only the most relevant context, thereby facilitating the review and application of AI-generated code alterations as diffs instead of requiring rewrites of entire files, which ensures meticulous and traceable modifications. Additionally, it features a visual file explorer for efficient project navigation, an intelligent context builder, and CodeMaps that minimize token usage while enhancing the models' comprehension of project structures. Users benefit from multi-model support, enabling them to utilize their own API keys from various providers such as OpenAI, Anthropic, Gemini, and Azure, ensuring that all processing remains local and private unless the user chooses to send code to a language model. Repo Prompt is versatile, functioning as both an independent chat/workflow interface and as an MCP (Model Context Protocol) server, allowing for seamless integration with AI editors, making it an essential tool in modern software development. Overall, its robust features significantly streamline the coding process while maintaining a strong emphasis on user control and privacy.

SuperDesign is an innovative AI-driven design tool that facilitates the creation of high-quality user interface mockups, reusable components, wireframes, and frontend code by transforming simple natural language inputs into visual assets. This solution empowers both designers and developers to streamline their workflow, significantly reducing the need to switch between applications like Figma and coding platforms, effectively integrating design generation into their development processes. Designed as an open-source agent, SuperDesign operates within widely-used development environments and code editors, such as Cursor, Windsurf, and Visual Studio Code. By leveraging large language models, it can accurately interpret user prompts to produce tailored visual designs and organized outputs that align with a project’s specific requirements, allowing teams to generate and evaluate multiple design options simultaneously for enhanced creative exploration. Additionally, SuperDesign offers the capability to import live web pages or individual UI components, converting them into editable designs or neatly organized code workspaces, thus further enhancing its utility in modern design and development contexts. This multifunctionality makes SuperDesign an essential asset for teams aiming to maximize their efficiency and creativity in the digital product development lifecycle.

Zernio is a unified social media API platform that enables developers and AI agents to publish, schedule, and manage content across 14+ social networks through a single integration. Instead of building and maintaining separate integrations with each platform's API, developers make one API call and Zernio handles authentication, media formatting, rate limits, and platform-specific requirements. The platform supports Instagram Business and Creator APIs, TikTok Business API, LinkedIn Company and Personal APIs, YouTube Data API, Twitter/X API, Facebook Graph API, Meta Business Suite, Pinterest API, Google My Business API, Reddit API, Threads API, Bluesky API, and WhatsApp Business API. Key capabilities include post scheduling and publishing, content management across all platforms, comments and DMs automation, analytics tracking, ads management, media upload and management, webhook notifications, rate limit management, and automatic token refresh. Zernio is designed for developers and technical teams building products that require social media functionality, including SaaS companies embedding social features into their own products, agencies managing client accounts at scale, and AI agent builders who need programmatic social posting. The product is white-label, meaning end users never see Zernio branding. Developer-friendly SDKs and comprehensive API documentation support fast implementation, reducing integration time from months to under an hour. A free version and free trial are available, with usage-based pricing.

Obot functions as an open-source AI infrastructure platform and Model Context Protocol (MCP) gateway, providing organizations with a centralized control system to discover, onboard, manage, secure, and scale MCP servers, which facilitate the connection of large language models and AI agents to various enterprise systems, tools, and data sources. It incorporates an MCP gateway, a catalog, an administrative console, and an optional integrated chat interface, all within a modern design that works seamlessly with identity providers like Okta, Google, and GitHub to implement access control, authentication, and governance policies across MCP endpoints, thus ensuring that AI interactions remain secure and compliant. Moreover, Obot empowers IT teams to host both local and remote MCP servers, manage access through a secure gateway, establish detailed user permissions, log and audit usage effectively, and create connection URLs for LLM clients, including tools like Claude Desktop, Cursor, VS Code, or custom agents, enhancing operational flexibility and security. Additionally, this platform streamlines the integration of AI services, making it easier for organizations to leverage advanced technologies while maintaining robust governance and compliance standards.

DeployStack is an enterprise-oriented management platform for Model Context Protocol (MCP) that aims to centralize, secure, and enhance the governance of MCP servers and AI tools within organizations. It features a unified dashboard that allows for the management of all MCP servers, incorporating centralized credential vaulting to eliminate the need for scattered API keys and manual configuration files, while also implementing role-based access control, OAuth2 authentication, and top-tier encryption to ensure secure enterprise operations. The platform provides detailed usage analytics and observability, delivering real-time insights into the utilization of MCP tools, including user access patterns and frequency, alongside comprehensive audit logs to support compliance and visibility into costs. Additionally, DeployStack optimizes token and context window management, enabling Large Language Model (LLM) clients to utilize significantly fewer tokens by employing a hierarchical routing system for accessing multiple MCP servers, thus maintaining model performance without compromise. This innovative approach not only streamlines operations but also empowers organizations to efficiently manage their AI resources while ensuring security and compliance.

Peta serves as an advanced control plane for the Model Context Protocol (MCP), streamlining, securing, governing, and overseeing how AI clients and agents interact with external tools, data, and APIs. This platform integrates a zero-trust MCP gateway, a secure vault, a managed runtime environment, a policy engine, human-in-the-loop approvals, and comprehensive audit logging into a cohesive solution, enabling organizations to implement nuanced access controls, safeguard raw credentials, and monitor all tool interactions conducted by AI systems. At the heart of Peta is Peta Core, which functions as both a secure vault and gateway, encrypting credentials, generating short-lived service tokens, verifying identity and compliance with policies for each request, managing the MCP server lifecycle through lazy loading and auto-recovery, and injecting credentials during runtime without revealing them to agents. Additionally, the Peta Console empowers teams to specify which users or agents can access particular MCP tools within designated environments, establish approval protocols, manage tokens, and review usage statistics and associated costs. This multifaceted approach not only enhances security but also fosters efficient resource management and accountability within AI operations.

Pencil.dev is an innovative design-in-code platform that utilizes AI to seamlessly integrate visual interface design within development environments such as Cursor, VS Code, and various other IDEs, allowing designers and developers to collaborate without the need for tool handoffs. Centered around an agent-driven Model Context Protocol (MCP) canvas and an accessible design format embedded in your codebase, Pencil enables users to create, refine, and produce pixel-perfect UI screens with the aid of AI, all while maintaining version control in Git alongside their source code, which facilitates branches, merges, and rollbacks akin to traditional coding practices. By incorporating a Figma-like canvas directly into the IDE, it significantly reduces the hassle of switching between different tools, supports the import of frames and assets from Figma while preserving vectors and styles, and allows for manipulation of design elements through intuitive editing panels, layers, and CSS-like properties. Furthermore, AI models assist in the simultaneous generation of screens, flows, and components, enhancing productivity and creativity in the design process. This integration fosters a more cohesive workflow, making it easier for teams to innovate and iterate on their projects efficiently.